Project Summary Cancer is a complex disease at both molecular and cellular levels. Cancer biology involves disruptions across all levels of molecular cell signaling, including proteins, mRNA, and even energy sources, or metabolites. Tumors are also highly heterogeneous mixtures of cells that become more heterogeneous over time due to the genomic instability of cancer cells. With these two levels of complexity, cancer is difficult to treat because the molecular mechanisms of cancer are poorly understood, and treatments stop short of cures because they kill some but not all of the heterogeneous tumor cell population. Currently, single cell techniques measure one type of data, such as the amount of specific proteins in each cell, to help determine how cancer cells function and how they can be targeted with treatments. Compared to bulk level measurements, which measure the average protein level across a tumor, single cell measurements can detect cell subpopulations that would be lost in an averaged measurement, which may include cancer stem cells or cells that resist treatments. This allows treatments to be designed that are more specific and effective for each tumor or patient. This proposal will lead to a better understanding of cancer cell function by simultaneously gathering proteomic, transcriptomic, and metabolomic data for the first time, and it will lead to improved detection and treatment of tumors by gathering these three types of data at the single cell level, thus revealing the heterogeneity of the tumor. In the short term, this proposal focuses on the development of a microfluidic platform for protein and metabolite quantification that integrates bead-based transcriptome sequencing. Integrating these three types of measurements requires a combination of a microchip-based platform for measuring proteins and metabolites and a bead-based platform for sequencing mRNA. By capturing each cell?s mRNA on beads and labeling beads with DNA-encoded location tags, sequenced mRNA can be traced back to a microfluidic chamber where the proteins and metabolites are captured and measured. The platform will initially be applied to a brain cancer system, glioblastoma multiforme (GBM), to study its response to therapeutic inhibitors and the development of drug resistance. In the long term, this technique can be applied to different heterogeneous biological systems to generate novel insights on multi-level signaling pathways.